In 2005, the United States announced a record 43,200 traffic related deaths. Many of these accidents could be prevented if the driver had been warned of the impending danger. A disproportionately high number of these deaths are the result of head on collisions at night. There are many reasons for the high number of deadly collisions at night. As can be appreciated, drivers often become tired at night, headlights can blind drivers, many animals are nocturnal, and on a two lane road it is often difficult for a driver to determine if an oncoming car is on a collision course with the driver. In nearly all of these instances, if the driver could be warned of the impending danger, the driver could take corrective action and many such deaths could be avoided.
As we can all appreciate, even the most cautious drivers make mistakes, and further, reckless drivers are the biggest threat to safe drivers. For example, unsafe drivers may run a red light, not yield when they should, not stop when they should, travel too close, change lanes or direction suddenly, and swerve or wander into an adjacent lane. Arguably, the added distraction of mobile telephone usage while driving has made our roads even more dangerous. Other phenomena such as not seeing vehicles in a blind spot, not seeing ice or water on the road ahead, falling asleep, avoiding animals or debris on the road, and going too fast or exceeding the posted speed limit can all contribute to collisions, accidents and even death.
Collision detection systems and collision avoidance systems for vehicles have been attempted for many years, and in the 1990's the United States Department of Transportation (USDOT)'s National Highway Traffic Safety Administration (NHTSA) funded research on such systems and reported on the efforts and advances for Automotive Collision Avoidance Systems (ACAS) for the ACAS program. In this cost-shared project, NHTSA partnered with a consortium of corporations such as Ford and General Motors. Such an ACAS system is relatively complex and utilizes technologies such as forward radar sensing to detect and report objects that could cause possible collisions with the system vehicle.
The ACAS program has focused on implementing a “comprehensive” collision warning system, capable of detecting and warning the driver of hazardous situations to the front, sides, and rear of the vehicle. This approach used long range radar and various sensors for forward sensing, short range sensors for lane changes and backing up, and a lane detection system. Development in this comprehensive research is limited to providing warnings to the driver, and not taking active control of the vehicle based on detecting potential collision information. These radar based solutions are currently being developed in an attempt to reduce the number of accidents by providing a driver with collision warnings. For example, such as system can warn a driver of a vehicle in a driver's blind spot.
One of the drawbacks to current collision warning systems is the common occurrence of false alarms. Such false alarms can be caused by objects such as roadside signs or guardrails on a curvy road or detection of a car in an adjacent lane on a curved portion of the road. Also, radar systems lack sufficient resolution to distinguish and identify different objects. For example, a radar based systems often cannot distinguish a large truck from a motorcycle. These radar based collision warning systems act on the principle that enabling drivers to recognize their environment will enhance their safety but these systems lack sufficient resolution to provide the desired detail and accuracy of situations to the driver.
An additional category of collision warning systems focus on run-off-the-road crashes by monitoring the driver, and can detect and warns of drowsiness, inebriation or other impairments that may prevent the driver from safely operating the vehicle. These systems are being deployed most widely in trucks, because of the high costs of fatigue and drowsiness related crashes.
As stated above, collision warning system that make inaccurate assumptions or do not have adequate resolution do not make accurate warning to drivers and often provide false warnings that eventually become distracting. Such a system is generally counter productive to the main goal of informing a driver because frequent false warnings often lull a driver into ignoring the warning system.